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Due to the current circumstances of COVID-19, we postponed the hands-on workshops and training sessions for single cell omics.
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UPCOMING SINGLE CELL TRAINING PROGRAMS

1

single cell omics:

data acquisition and pre-processing

Hands-on workshop on how to eﬃciently acquire and process data starting from count matrices:

- Preprocessing, quality control and basic analysis of tutorial data, publicly available data or own data.
- Introduction to visualisation tools, browsers and public data repositories.

data types:

scRNA-seq, CITEseq, hashing, scATAC-seq (human, mouse and plants)

target audience:

The training is aimed at scientists with a molecular biology background, an online teaching module (3h) to introduce R/Rstudio should be followed before the workshop.

timing:

H2 2021

2

single cell omics:

data mining

Dig deeper and provide a deeper insight into your single cell data with a data mining toolbox:

- annotation of cell populations
- heterogeneity analysis, diﬀerential gene expression and detection of meaningful cell populations across samples and conditions
- single cell data visualisations
- getting the most out of ggplot
- pseudotime ordering, trajectory inference
- cell-cell communication networks (NicheNet)
- regulatory networks (SCENIC)
- ...

data types:

scRNA-seq, CITEseq, hashing, scATAC-seq (human, mouse and plants)

target audience:

- beginners (after completion module 1)
- bioinformaticians

timing:

H2 2021

3

single cell omics:

advanced computational workflows

Advanced data analysis workﬂows for single cell data (R, python, Nextflow DSL2)

data types:

scRNA-seq, CITEseq, hashing, scATAC-seq (own data or tutorial data)

target audience:

bioinformaticians

timing:

H2 2021

4

spatial transcriptomics:

data visualisation and exploration

Hands-on workshop on how to explore, analyse and visualize spatial transcriptomics data, with the focus on Visium (10X Genomics) and provide examples for CARTANA and Slide-seq.

data types:

spatial transcriptomics, integration with scRNA-seq

target audience:

Bioinformaticians and scientists with a molecular biology background, an online teaching module (3h) to introduce Rstudio should be followed before the workshop.

timing:

H1 2022